Improvement of distance relay zone-3 security using fault and breaker opening generated traveling waves

Sharafi, A.R.; Sanaye‐Pasand, M.; Jafarian, Peyman

doi:10.1002/etep.2414

Cited by 9 publications

(6 citation statements)

References 27 publications

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“…Outages like generator outage, planned line outage, line faults, and relay maloperations are some of the factors that cause stress in the system [2]. The malfunction and stress caused in the system leads to power system outages [3,4]. Algorithms depending on the rate of progress of voltage and high-frequency substance of signals are proposed to recognize faults from other stressed occasions [5,6].…”

Section: Imentioning

confidence: 99%

Classification of Electrical Power System Conditions with Convolutional Neural Networks

Kiruthika¹,

Bindu²

2020

Eng. Technol. Appl. Sci. Res.

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Undesirable operation of a distant relay at the occurrence of stressed conditions is a reason for blackouts. There are a few computational intelligent methods available in the literature for avoiding relay maloperations. However, because of variations in the system parameters and expansions of the network, the performance of these techniques can be degraded. To solve this issue, data mining approaches have been introduced. The existing data mining approaches need improvement in terms of accuracy and error rate while discriminating fault and stressed conditions. In this paper, a Convolutional Neural Network (CNN) based classifier is proposed for identifying various faults and differentiating fault and power swing situations. The data are collected from the IEEE-9 bus system by Phasor Measurement Units (PMU) and the proposed CNN classifier model classifies system conditions like normal, fault, and power swing. The outcome shows that the classifier has high accuracy and low error rate compared to other classification models such as Naïve Bayes, Decision Tree, and K-Nearest Neighbor. Furthermore, the proposed CNN model is validated with the use of TensorFlow framework to demonstrate its superior performance.

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Section: Imentioning

confidence: 99%

Classification of Electrical Power System Conditions with Convolutional Neural Networks

Kiruthika¹,

Bindu²

2020

Eng. Technol. Appl. Sci. Res.

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“…An algorithm based on some methods like 4 polarity comparison, a time synchronized pilot protection scheme and high-frequency unblocking is proposed in [3] for the protection of high-voltage transmission lines.A TW-based method is proposed in [4] for the protection of transmission lines with the presence of renewable energies. Wavelet transform (WT) is used in [5][6][7] for the extraction of TWs.…”

Section: Introductionmentioning

confidence: 99%

A new traveling-wave-based protection algorithm using intelligent systems

Hasheminejad

2020

Scientia Iranica

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A novel traveling-wave (TW)-based protection algorithm for power transmission lines using intelligent systems is proposed in this paper. The first part of the algorithm identifies internal faults from external ones and the other part is used for fault type classification and faulted phases selection. In order to extract TW signals, Teagerenergyoperator (TEO) is used. Then hidden Markov model (HMM) is utilized to identify internal faults from external faults according to the output of TEO. Fault type classification and faulted phases selection are other important tasks in protection algorithms. In this paper, a very accurate and robust classification algorithm based on fuzzy systems is presented. This algorithm uses different ratios of modal components of the faulted current signal as the input variable of fuzzy systems. The test system is simulated in PSCAD software and the algorithm is implemented in MATLAB. Testing the proposed algorithm with a large number of test signals in different fault conditions shows the robustness of both internal fault identification and fault type classification algorithms.

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“…To solve the problem using local data, some algorithms are proposed in the literature based on derivatives of voltage and current, fault and circuit breaker opening traveling waves, and derivative of impedance in combination with the conventional zone-3 scheme. [6][7][8][9][10] In Ma et al, 11 a blocking and re-opening scheme is proposed for distance relays to improve their performance during power swings based on calculating dynamic phasors through least squares optimization. A zone-3 protection scheme based on combining the steady state and transient components of the voltage signal has been discussed in Kim et al 12 However, for implementing such a high-frequency component-based method, special measurement devices are required.…”

Section: Introductionmentioning

confidence: 99%

“…The abovementioned methods in the literature [6][7][8][9][10][11][12] have the advantage of using local data. However, they could not consider all possible circumstances, because of their limited access to the power network data.…”

Section: Introductionmentioning

confidence: 99%

“…Mal‐operation of zone‐3 may occur during stressed system conditions where the measured impedance trajectory enters the operating characteristic and the relay is unable to discriminate between a fault and a stressed condition. To solve the problem using local data, some algorithms are proposed in the literature based on derivatives of voltage and current, fault and circuit breaker opening traveling waves, and derivative of impedance in combination with the conventional zone‐3 scheme . In Ma et al, a blocking and re‐opening scheme is proposed for distance relays to improve their performance during power swings based on calculating dynamic phasors through least squares optimization.…”

Section: Introductionmentioning

confidence: 99%

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Improved zone-3 distance protection based on adjacent relays data

Sharafi

Sanaye‐Pasand

Hashemi

2018

Int Trans Electr Energ Syst

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Summary A wide‐area backup protection (WABP) method is proposed in this paper based on the zone status of distance relays. The time difference between the operation of zone‐3 and wide‐area based methods makes it possible to employ wide‐area data for improvement of zone‐3. In case of zone‐3 is directly backup for zone‐1, the proposed method can decrease the time delay of zone‐3 with a complete reliability. Moreover, the proposed method is capable of discriminating between the actual faults and power system stressed conditions. Considering the operational time of wide‐area methods, the algorithm could also be applied for zone‐2 backup protection. The proposed method is also developed to consider the availability of wide‐area data for all busses within the disturbance area, as well as data missing for one or two adjacent busses, which are remarkable advantages over the existing WABP methods. Meanwhile, the wide‐area data used in the proposed method are only the pickup/release status of distance relays zones which are binary data and can be communicated readily through existing wide‐area infrastructures. Simulation results on the IEEE 57‐bus test system demonstrate the effectiveness of the proposed method as a promising WABP in improving the performance of zone‐3 in distance protection schemes.

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Improvement of distance relay zone-3 security using fault and breaker opening generated traveling waves

Cited by 9 publications

References 27 publications

Classification of Electrical Power System Conditions with Convolutional Neural Networks

Classification of Electrical Power System Conditions with Convolutional Neural Networks

A new traveling-wave-based protection algorithm using intelligent systems

Improved zone-3 distance protection based on adjacent relays data

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